GIS-enabled hydrocarbon prospect polygons for established (immature) and conceptual plays, Mackenzie Corridor, Northwest Territories and Yukon
Bibliographic record
Abstract
The hydrocarbon potential of the northern mainland sedimentary basin is the focus of a Northern Energy project under the Secure Canadian Energy Supply program of the Geological Survey of Canada (GSC). The main objective of this multidisciplinary study is to assess the hydrocarbon resource potential of the underexplored Mackenzie Corridor using quantitative and qualitative geoscience data. The petroleum assessment approach developed by the GSC requires the definition of exploration petroleum plays and compilation of reservoir parameters, such as distribution, size, and number of prospects. The present report compiles individual shapefiles outlining 19 established-immature and conceptual exploration plays located in the Mackenzie Valley and Mackenzie Mountains that are the focus of the GSC petroleum assessment study. A series of companion shapefiles identifying individual prospects have been constructed from available geophysical maps and include information such as the size, number, distribution, and vertical closures of the prospects. Prospect statistics presented in this report are based on 215 geophysical (time and depth structure, isopach) maps generated by the petroleum industry. This GIS compilation includes lines, polygons, attributes and raster images representing faults, exploration plays and associated prospects, geophysical maps and associated footprints. Results are presented using ArcReaderTM software which allows the user to build maps by selecting appropriate layers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".